Recent years have seen an explosion in the popularity and availability of social media platforms, such as social networking applications, web logs (“blogs”), message boards, interactive news websites, photo-sharing sites, etc. Social media allows users to interact with one another, such as by posting new content and/or by posting reactions to content posted by others. As such, social media platforms provide users with forums in which to engage in conversations with one another. A single user can have accounts, linked to user profiles, on multiple social media platforms.
The wealth of sentiment and opinion that exists on social media platforms is of great value to companies that wish to identify potential customers, to steer public sentiment regarding particular brands, to steer social trends, and/or to otherwise communicate with target customers in identifiable demographic groups.
However, the challenge of gathering and interpreting this valuable data is a significant, and as yet unsolved, problem. A single social media platform may include thousands of posts, organized into many different threads and posted by a combination of thousands of different users. Further, many users may each create content on multiple social networks. In many cases, conversations started on one platform may spill over onto another, different users may have different audiences, levels of influence, multiple usernames or multiple accounts, posts may express different sentiments or may be of varying levels of interest, etc. Many types of businesses stand to benefit greatly from gathering and understanding social media data.